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Wavelet Radar Signal Processing and its Applications to Industrial Roller Rotation Monitoring

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Abstract

In this article, attention is paid to the task of remote monitoring of the state of an industrial roller using radar. A millimeter-wave radar using an FMCW signal is used to assess the state of the roller rotation quality. A test bench has been developed and a dataset of test signals has been recorded. An approach to the analysis of recorded signals using digital processing based on Morlet wavelet and a deep learning neural network is proposed.

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Denis Valuyskiy has done the soft implementation. Sergey Vityazev and Denis Valuyskiy have completed the experimental part and wrote the manuscript. Vladimir Vityazev has reviewed the manuscript.

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Correspondence to Denis Valuyskiy.

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This article is part of the topical collection “Advance in Artificial Intelligence for Machine Vision Applications” guest edited by Koushlendra Kumar Singh, B. Ramchandra Reddy, V. M. Gadre and Akbar Sheikh Akbari.

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Valuyskiy, D., Vityazev, S. & Vityazev, V. Wavelet Radar Signal Processing and its Applications to Industrial Roller Rotation Monitoring. SN COMPUT. SCI. 5, 587 (2024). https://doi.org/10.1007/s42979-024-02897-z

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